Press Release:  Immediate Release



San Jose, CA

Sightech Vision Systems, Inc.              

408 2823770

Attn:  Art Gaffin or Tom Seitzler


Subject:  Fluid flow contaminants inspection


San Jose, CA   September 14, 2005


The Sightech PC Eyebot was recently applied successfully to an application that demanded the finding of bubbles in a container of water.   This seemingly simple application has important implications for liquid inspections of many varieties. 


The requirement was to identify bubbles of any type, size, location, shape or orientation within the segment of the camera’s working area.  A simple 640 x 480 camera was used.  There were all types of reflections on the water, and a variety of waves in various directions and amplitudes from the breaking bubbles.   The PC Eyebot was required to “LEARN” (train) on the bubbles, then “FORGET” (ignore) normal conditions of the water. 


The three attached images show the process of training, forgetting, and then inspecting.  These images, additional explanation, and a tutorial on setting up an application on the PC Eyebot can be viewed at  The camera was placed; “emphasis” and feature characteristics were selected to clearly define objects of interest.  The bubbles showed clearly.  Next the “FORGET” mode was selected and the water, without the bubbles, was forgotten by the Eyebot inspection processor.   When the Eyebot was placed in “RECOGNIZE” mode, bubbles were recognized and deemed “present” where flat water, or water without the bubbles resulted in an “absent” condition.  The user can determine how many bubbles are needed to trigger a “present” judgment. 


The random characteristics of the bubbles made this an especially difficult application for any other  type of inspection system.  The glare from the water, and the continuously changing background, as well as variable lighting added to the challenge. 


Given sensors with proper sensitivities, many contaminants can be detected either on or in fluid flows of this type. 


This bubble detection is another example that is leading the market to agree with the complimentary judgment:   “If you or I can recognize it, so can the PC Eyebot”.